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Record W2007277005 · doi:10.1155/2014/943219

Smoke Exposure Has Transient Pulmonary and Systemic Effects in Wildland Firefighters

2014· article· en· W2007277005 on OpenAlexaffabout
Sandra C. Dorman, Stacey A. Ritz

Bibliographic record

VenueJournal of Respiratory Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsNOSM UniversityLaurentian University
Fundersnot available
KeywordsSmokeMedicineAcute exposureFirefightingRespiratory systemSputumSystemic inflammationPhysiologyEnvironmental healthInternal medicineInflammationPathologyChemistry

Abstract

fetched live from OpenAlex

Respiratory exposure to air pollutants is associated with cardiovascular morbidity and mortality and firefighters have been shown to be at an increased risk of work-related cardiovascular events. Wildland firefighters experience intermittent, intense exposure to biomass smoke. The aim of this study was to characterize the respiratory and systemic effects of smoke exposure in wildland firefighters. Seventeen seasonal firefighters from a northeastern Ontario community were recruited at the beginning of the fire season and baseline measurements obtained; postexposure measurements were made at various times within 16 d of firefighting. Spirometric measurements showed a transient decline in forced vital capacity within 7 d of fire exposure, not evident by 8–16 d. Induced sputum showed a significant increase in macrophages and epithelial cells within 7 d, with evidence that macrophages had internalized particles; such changes were not evident in the second week following exposure. Likewise, peripheral blood analysis revealed significant increases in erythrocytes, hemoglobin, monocytes, and platelets within the first week after fire exposure, which were diminished 8–16 d in postexposure group. We conclude that acute exposure to forest-fire smoke elicits transient inflammatory responses, both in the airways and systemically. Whether these changes contribute to the observed increased risk of cardiovascular events requires further study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.384
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2014
Admission routes2
Has abstractyes

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